@inproceedings{smirnov-2019-neural,
    title = "Neural Network-based Models with Commonsense Knowledge for Machine Reading Comprehension",
    author = "Smirnov, Denis",
    editor = "Kovatchev, Venelin  and
      Temnikova, Irina  and
      {\v{S}}andrih, Branislava  and
      Nikolova, Ivelina",
    booktitle = "Proceedings of the Student Research Workshop Associated with RANLP 2019",
    month = sep,
    year = "2019",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/R19-2014/",
    doi = "10.26615/issn.2603-2821.2019_014",
    pages = "90--94",
    abstract = "State-of-the-art machine reading comprehension models are capable of producing answers for factual questions about a given piece of text. However, some type of questions requires commonsense knowledge which cannot be inferred from the given text passage. Thus, external semantic information could enhance the performance of these models. This PhD research proposal provides a brief overview of some existing machine reading comprehension datasets and models and outlines possible ways of their improvement."
}